Finally, and due to relevancy to our topic, we briefly mention the background of continuous optimization-based causal discovery methods. Unlike score-based methods, this class of algorithms avoids the combinatorial greedy search over DAGs by employing gradient-based approaches. DAGs with NO TEARS [1]} is typically considered as the first to reformulate graph search problem as a continuous optimization problem [2]}. DAG-GNN [3]} extends NO TEARS by incorporating deep learning to capture complex nonlinear mappings. They propose a deep generative model and apply a variant of the structural constraint to learn the underlying causal structure.
